1. Field of the Invention
The present invention relates to an estimation method for a predicted motion vector, and more particularly, to an estimation method for estimating a predicted motion vector via difference information between frames.
2. Description of the Prior Art
Motion estimation is an important technique in video compression, its objective being to determine a motion vector using a correlation between a previous and subsequent frame, and to obtain the subsequent image frame accordingly, thereby reducing redundancy information in each image frame at different times. A video is a series of image frames played back consecutively, and its primary working principle is to create an illusion of animation via transient visual persistence of the subtle variations between neighboring image frames. Generally, neighboring frames exhibit a strong correlation with each other in time and space, and usually have portions that are similar or identical to each. Therefore, when storing or transmitting image frames, the identical parts without variation do not need to be stored. After recording previous frames, a subsequent frame may be reconstructed using the stored previous frame and information recorded during the object motion process. In other words, during video encoding/decoding, not all of the frame information needs to be processed, thereby effectively reducing transmission throughput, and achieving video compression.
Block matching is a common method for calculating a motion vector, in which an image frame is divided into multiple non-overlapping blocks, and similar portions in each block at different times are identified to obtain the motion vector information for each block. Various search algorithms have been proposed in the prior art for determining correlation information of motion vectors. For example, algorithms such as Full Search, Three Step Search, Four Step Search, Diamond Search, Three Dimensional Recursive Search, or Cross Search may be used to obtain correlation information for a motion vector, and then the predicted motion vector may be obtained via match estimation (e.g. sum of absolute difference (SAD) computation) to implement optimal block matching. However, despite the ability to provide more accurate motion vectors, block matching methods incur longer search time and more complex computations, and thus do not suit real-time applications.
In such a case, phase plane correlation has been proposed in the prior art to implement faster motion vector estimation, which primarily converts the video image from spatial domain to frequency domain, and directly compare phase differences of two image frames in the frequency domain to perform motion vector estimation. However, phase plane correlation methods require performing Fast Fourier Transform (FFT) for conversion, which also consumes excessive system resources and computation time, and thus they are not suit for real-time applications.